Efficient Kernel-Based Ensemble Gaussian Mixture Filtering
نویسندگان
چکیده
منابع مشابه
Gaussian Mixture Model-Based Ensemble Kalman Filtering for State and Parameter Estimation for a PMMA Process
Abstract: Polymer processes often contain state variables whose distributions are multimodal; in addition, the models for these processes are often complex and nonlinear with uncertain parameters. This presents a challenge for Kalman-based state estimators such as the ensemble Kalman filter. We develop an estimator based on a Gaussian mixture model (GMM) coupled with the ensemble Kalman filter ...
متن کاملKernel Trick Embedded Gaussian Mixture Model
In this paper, we present a kernel trick embedded Gaussian Mixture Model (GMM), called kernel GMM. The basic idea is to embed kernel trick into EM algorithm and deduce a parameter estimation algorithm for GMM in feature space. Kernel GMM could be viewed as a Bayesian Kernel Method. Compared with most classical kernel methods, the proposed method can solve problems in probabilistic framework. Mo...
متن کاملSpeech Enhancement Using Gaussian Mixture Models, Explicit Bayesian Estimation and Wiener Filtering
Gaussian Mixture Models (GMMs) of power spectral densities of speech and noise are used with explicit Bayesian estimations in Wiener filtering of noisy speech. No assumption is made on the nature or stationarity of the noise. No voice activity detection (VAD) or any other means is employed to estimate the input SNR. The GMM mean vectors are used to form sets of over-determined system of equatio...
متن کاملA tree-based kernel selection approach to efficient Gaussian mixture model-universal background model based speaker identification
We propose a tree-based kernel selection (TBKS) algorithm as a computationally efficient approach to the Gaussian mixture model–universal background model (GMM–UBM) based speaker identification. All Gaussian components in the universal background model are first clustered hierarchically into a tree and the corresponding acoustic space is mapped into structurally partitioned regions. When identi...
متن کاملGaussian mixture optimization for HMM based on efficient cross-validation
A Gaussian mixture optimization method is explored using cross-validation likelihood as an objective function instead of the conventional training set likelihood. The optimization is based on reducing the number of mixture components by selecting and merging a pair of Gaussians step by step base on the objective function so as to remove redundant components and improve the generality of the mod...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Monthly Weather Review
سال: 2016
ISSN: 0027-0644,1520-0493
DOI: 10.1175/mwr-d-14-00292.1